25 resultados para soil sampling intensity

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Mineral exploration programmes around the world use data from remote sensing, geophysics and direct sampling. On a regional scale, the combination of airborne geophysics and ground-based geochemical sampling can aid geological mapping and economic minerals exploration. The fact that airborne geophysical and traditional soil-sampling data are generated at different spatial resolutions means that they are not immediately comparable due to their different sampling density. Several geostatistical techniques, including indicator cokriging and collocated cokriging, can be used to integrate different types of data into a geostatistical model. With increasing numbers of variables the inference of the cross-covariance model required for cokriging can be demanding in terms of effort and computational time. In this paper a Gaussian-based Bayesian updating approach is applied to integrate airborne radiometric data and ground-sampled geochemical soil data to maximise information generated from the soil survey, to enable more accurate geological interpretation for the exploration and development of natural resources. The Bayesian updating technique decomposes the collocated estimate into a production of two models: prior and likelihood models. The prior model is built from primary information and the likelihood model is built from secondary information. The prior model is then updated with the likelihood model to build the final model. The approach allows multiple secondary variables to be simultaneously integrated into the mapping of the primary variable. The Bayesian updating approach is demonstrated using a case study from Northern Ireland where the history of mineral prospecting for precious and base metals dates from the 18th century. Vein-hosted, strata-bound and volcanogenic occurrences of mineralisation are found. The geostatistical technique was used to improve the resolution of soil geochemistry, collected one sample per 2 km2, by integrating more closely measured airborne geophysical data from the GSNI Tellus Survey, measured over a footprint of 65 x 200 m. The directly measured geochemistry data were considered as primary data in the Bayesian approach and the airborne radiometric data were used as secondary data. The approach produced more detailed updated maps and in particular maximized information on mapped estimates of zinc, copper and lead. Greater delineation of an elongated northwest/southeast trending zone in the updated maps strengthened the potential to investigate stratabound base metal deposits.

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A substantial proportion of aetiological risks for many cancers and chronic diseases remain unexplained. Using geochemical soil and stream water samples collected as part of the Tellus Project studies, current research is investigating naturally occurring background levels of potentially toxic elements (PTEs) in soils and stream sediments and their possible relationship with progressive chronic kidney disease (CKD). The Tellus geological mapping project, Geological Survey Northern Ireland, collected soil sediment and stream water samples on a grid of one sample site every 2 km2 across the rural areas of Northern Ireland resulting in an excess of 6800 soil sampling locations and more than 5800 locations for stream water sampling. Accumulation of several PTEs including arsenic, cadmium, chromium, lead and mercury have been linked with human health and implicated in renal function decline. The hypothesis is that long-term exposure will result in cumulative exposure to PTEs and act as risk factor(s) for cancer and diabetes related CKD and its progression. The ‘bioavailable’ fraction of total PTE soil concentration depends on the ‘bioaccessible’ proportion through an exposure pathway. Recent work has explored this bioaccessible fraction for a range of PTEs across Northern Ireland. In this study the compositional nature of the multivariate geochemical PTE variables and bioaccessible data is explored to augment the investigation into the potential relationship between PTEs, bioaccessibility and disease data.

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This study applies spatial statistical techniques including cokriging to integrate airborne geophysical (radiometric) data with ground-based measurements of peat depth and soil organic carbon (SOC) to monitor change in peat cover for carbon stock calculations. The research is part of the EU funded Tellus Border project and is supported by the INTERREG IVA development programme of the European Regional Development Fund, which is managed by the Special EU Programmes Body (SEUPB). The premise is that saturated peat attenuates the radiometric signal from underlying soils and rocks. Contemporaneous ground-based measurements were collected to corroborate mapped estimates and develop a statistical model for volumetric carbon content (VCC) to 0.5 metres. Field measurements included ground penetrating radar, gamma ray spectrometry and a soil sampling methodology which measured bulk density and soil moisture to determine VCC. One aim of the study was to explore whether airborne radiometric survey data can be used to establish VCC across a region. To account for the footprint of airborne radiometric data, five cores were obtained at each soil sampling location: one at the centre of the ground radiometric equivalent sample location and one at each of the four corners 20 metres apart. This soil sampling strategy replicated the methodology deployed for the Tellus Border geochemistry survey. Two key issues will be discussed from this work. The first addresses the integration of different sampling supports for airborne and ground measured data and the second discusses the compositional nature of the VOC data.

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The results of a study aimed at determining the most important experimental parameters for automated, quantitative analysis of solid dosage form pharmaceuticals (seized and model 'ecstasy' tablets) are reported. Data obtained with a macro-Raman spectrometer were complemented by micro-Raman measurements, which gave information on particle size and provided excellent data for developing statistical models of the sampling errors associated with collecting data as a series of grid points on the tablets' surface. Spectra recorded at single points on the surface of seized MDMA-caffeine-lactose tablets with a Raman microscope (lambda(ex) = 785 nm, 3 mum diameter spot) were typically dominated by one or other of the three components, consistent with Raman mapping data which showed the drug and caffeine microcrystals were ca 40 mum in diameter. Spectra collected with a microscope from eight points on a 200 mum grid were combined and in the resultant spectra the average value of the Raman band intensity ratio used to quantify the MDMA: caffeine ratio, mu(r), was 1.19 with an unacceptably high standard deviation, sigma(r), of 1.20. In contrast, with a conventional macro-Raman system (150 mum spot diameter), combined eight grid point data gave mu(r) = 1.47 with sigma(r) = 0.16. A simple statistical model which could be used to predict sigma(r) under the various conditions used was developed. The model showed that the decrease in sigma(r) on moving to a 150 mum spot was too large to be due entirely to the increased spot diameter but was consistent with the increased sampling volume that arose from a combination of the larger spot size and depth of focus in the macroscopic system. With the macro-Raman system, combining 64 grid points (0.5 mm spacing and 1-2 s accumulation per point) to give a single averaged spectrum for a tablet was found to be a practical balance between minimizing sampling errors and keeping overhead times at an acceptable level. The effectiveness of this sampling strategy was also tested by quantitative analysis of a set of model ecstasy tablets prepared from MDEA-sorbitol (0-30% by mass MDEA). A simple univariate calibration model of averaged 64 point data had R-2 = 0.998 and an r.m.s. standard error of prediction of 1.1% whereas data obtained by sampling just four points on the same tablet showed deviations from the calibration of up to 5%.

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Agricultural soils are the dominant contributor to increases in atmospheric nitrous oxide (N2O). Few studies have investigated the natural N and O isotopic composition of soil N2O. We collected soil gas samples using horizontal sampling tubes installed at successive depths under five contrasting agricultural crops (e.g., unamended alfalfa, fertilized cereal), and tropospheric air samples. Mean d 15N and d 18O values of soil N2O ranged from -28.0 to +8.9‰, and from +29.0 to +53.6‰. The mean d 15N and d 18O values of tropospheric N2O were +4.6 ± 0.7‰ and +48.3 ± 0.2‰, respectively. In general, d values were lowest at depth, they were negatively correlated to soil [N2O], and d 15N was positively correlated to d 18O for every treatment on all sampling dates. N2O from the different agricultural treatments had distinct d 15N and d 18O values that varied among sampling dates. Fertilized treatments had soil N2O with low d values, but the unamended alfalfa yielded N2O with the lowest d values. Diffusion was not the predominant process controlling N2O concentration profiles. Based on isotopic and concentration data, it appears that soil N2O was consumed, as it moved from deeper to shallower soil layers. To better assess the main process(es) controlling N2O within a soil profile, we propose a conceptual model that integrates data on net N2O production or consumption and isotopic data. The direct local impact of agricultural N2O on the isotopic composition of tropospheric N2O was recorded by a shift toward lower d values of locally measured tropospheric N2O on a day with very high soil N2O emissions.

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The validity of load estimates from intermittent, instantaneous grab sampling is dependent on adequate spatial coverage by monitoring networks and a sampling frequency that re?ects the variability in the system under study. Catchments with a ?ashy hydrology due to surface runoff pose a particular challenge as intense short duration rainfall events may account for a signi?cant portion of the total diffuse transfer of pollution from soil to water in any hydrological year. This can also be exacerbated by the presence of strong background pollution signals from point sources during low flows. In this paper, a range of sampling methodologies and load estimation techniques are applied to phosphorus data from such a surface water dominated river system, instrumented at three sub-catchments (ranging from 3 to 5 km2 in area) with near-continuous monitoring stations. Systematic and Monte Carlo approaches were applied to simulate grab sampling using multiple strategies and to calculate an estimated load, Le based on established load estimation methods. Comparison with the actual load, Lt, revealed signi?cant average underestimation, of up to 60%, and high variability for all feasible sampling approaches. Further analysis of the time series provides an insight into these observations; revealing peak frequencies and power-law scaling in the distributions of P concentration, discharge and load associated with surface runoff and background transfers. Results indicate that only near-continuous monitoring that re?ects the rapid temporal changes in these river systems is adequate for comparative monitoring and evaluation purposes. While the implications of this analysis may be more tenable to small scale ?ashy systems, this represents an appropriate scale in terms of evaluating catchment mitigation strategies such as agri-environmental policies for managing diffuse P transfers in complex landscapes.

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Seismic geophysical methods have rarely been used in precision agriculture, predominantly due to the perception that they are slow and results require a complex evaluation. This paper explores the possibility of using a recently developed surface wave seismic geophysical approach, the multichannel analysis of surface waves (MASW) method, for assessment of agricultural compaction. This approach has the advantage of being non-intrusive, rapid and is able to produce 2D ground models with a relatively high density of spatial sampling points. The method, which was tested on a research site in Oakpark, Ireland, detected a significant difference in shear wave velocity between a heavily compacted headland and an uncompacted location. The results from this approach compared favourably with those obtained
from measurements of bulk density and penetrometer resistance and demonstrate that the MASW approach can distinguish between the extreme states of heavily compacted and uncompacted soil.

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Arsenic volatilization in the environment is thought to be an important pathway for transfer from terrestrial pools to the atmosphere. However, this phenomenon is not well characterized due to inherent sampling issues in trapping, quantifying and qualifying these arsine gases; including arsine (AsH(3)), monomethyl arsine (MeAsH(2)), dimethyl arsine (Me(2)AsH) and trimethyl arsine (TMAs). To quantify and qualify arsines in air we developed a novel technique based on silver nitrate impregnated silica gel filled tubes. The method was characterized by measuring the recovery of trapped arsines after elution of this chemo-trap with hot boiling diluted nitric acid. Results from three separate experiments, measured by ICP-MS, showed that the method is reproducible and quantitative. Arsine species recovery ranged from 80.1 to 95.6%, with limit of detection as low as 3.8 ng per chemo-trap tube. Moreover, HPLC-ICP-MS analysis of hot boiling water eluted traps showed that the corresponding oxy ions of the arsines were formed with the As-C bonds of the molecule intact, hence, allowing qualification of trapped arsine species. A microcosm study examining volatile arsenic evolution from field contaminated Bangladeshi paddy soils (24.2 mg/kg arsenic) was used to show the application of silver nitrate chemo-trapping approach. Traps were placed on the inlet and the outlet of microcosms containing the soils that were either (cattle derived) manured or not, or flooded or not, in a factorial design. The headspace was purged with air at a flow rate of 12 mL/min. Results showed that as much as 320 ng of arsenic (0.014% of total soil content) could be emitted in a 3 week period for manured and flooded soils and that TMAs was the dominant species evolved, with lesser quantities of Me(2)AsH. No volatile arsenic evolution was observed for nonmanured treatments, and arsine release from the nonflooded, manured treatment was much less than the flooded treatment.

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Greylag geese (Anser anser) in the Guadalquivir Marshes (southwestern Spain) can be exposed to sources of inorganic pollution such as heavy metals and arsenic from mining activities or Pb shot used for hunting. We have sampled 270 fecal excreta in different areas of the marshes in 2001 to 2002 to evaluate the exposure to Pb, Zn, Cu, Mn, and As and to determine its relationship with soil ingestion and with the excretion of porphyrins and biliverdin as biomarkers. These effects and the histopathology of liver, kidney, and pancreas were also studied in 50 geese shot in 2002 to 2004. None of the geese had ingested Pb shot in the gizzard. This contrasts with earlier samplings before the ban of Pb shot for waterfowl hunting in 2001 and the removal of Pb shot in points of the Doñana National Park (Spain) in 1999 to 2000. The highest exposure through direct soil ingestion to Pb and other studied elements was observed in samples from Entremuros, the area of the Doñana Natural Park affected by the Aznalcóllar mine spill in 1998. Birds from Entremuros also more frequently showed mononuclear infiltrates in liver and kidney than birds from the unaffected areas, although other more specific lesions of Pb or Zn poisoning were not observed. The excretion of coproporphyrins, especially of the isomer I, was positively related to the fecal As concentration, and the ratio of coproporphyrin III/I was positively related to fecal Pb concentration. Biliary protoporphyrin IX concentration was also slightly related to hepatic Pb concentration. This study reflects biological effects on terrestrial animals by the mining pollution in Doñana that can be monitored with the simple noninvasive sampling of feces.

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Polycyclic aromatic hydrocarbons (PAHs) were determined in soil and vegetation following a large scale chemical fire involving 10,000 ton of polypropylene. In comparison with sites outside the plume from the fire, PAH concentrations were elevated in grass shoots (by up to 70-fold) and in soil (by up to 370-fold). The pattern of PAH dispersion under the plume was dependent on the physical-chemical properties of individual PAHs. The lighter, least hydrophobic PAHs were dispersed into the environment at greater distances than heavier, more hydrophobic PAHs. At the most distant sampling point (4.5 km) under the plume, the low molecular weight PAHs were still considerably elevated in vegetation samples compared to control sites. Dispersion appeared to be regulated by the compounds partitioning between the vapour and particulate phase, with dry particulate deposition occurring closer to the fire source than gaseous deposition. For all PAHs, the fire resulted in greater contamination of soils compared to grasses, with the relative ratio of plant/soil contamination decreasing as hydrophobicity increased.

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1. Ecologists are debating the relative role of deterministic and stochastic determinants of community structure. Although the high diversity and strong spatial structure of soil animal assemblages could provide ecologists with an ideal ecological scenario, surprisingly little information is available on these assemblages.
2. We studied species-rich soil oribatid mite assemblages from a Mediterranean beech forest and a grassland. We applied multivariate regression approaches and analysed spatial autocorrelation at multiple spatial scales using Moran's eigenvectors. Results were used to partition community variance in terms of the amount of variation uniquely accounted for by environmental correlates (e.g. organic matter) and geographical position. Estimated neutral diversity and immigration parameters were also applied to a soil animal group for the first time to simulate patterns of community dissimilarity expected under neutrality, thereby testing neutral predictions.
3. After accounting for spatial autocorrelation, the correlation between community structure and key environmental parameters disappeared: about 40% of community variation consisted of spatial patterns independent of measured environmental variables such as organic matter. Environmentally independent spatial patterns encompassed the entire range of scales accounted for by the sampling design (from tens of cm to 100 m). This spatial variation could be due to either unmeasured but spatially structured variables or stochastic drift mediated by dispersal. Observed levels of community dissimilarity were significantly different from those predicted by neutral models.
4. Oribatid mite assemblages are dominated by processes involving both deterministic and stochastic components and operating at multiple scales. Spatial patterns independent of the measured environmental variables are a prominent feature of the targeted assemblages, but patterns of community dissimilarity do not match neutral predictions. This suggests that either niche-mediated competition or environmental filtering or both are contributing to the core structure of the community. This study indicates new lines of investigation for understanding the mechanisms that determine the signature of the deterministic component of animal community assembly.

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Biotic communities in Antarctic terrestrial ecosystems are relatively simple and often lack higher trophic levels (e. g. predators); thus, it is often assumed that species' distributions are mainly affected by abiotic factors such as climatic conditions, which change with increasing latitude, altitude and/or distance from the coast. However, it is becoming increasingly apparent that factors other than geographical gradients affect the distribution of organisms with low dispersal capability such as the terrestrial arthropods. In Victoria Land (East Antarctica) the distribution of springtail (Collembola) and mite (Acari) species vary at scales that range from a few square centimetres to regional and continental. Different species show different scales of variation that relate to factors such as local geological and glaciological history, and biotic interactions, but only weakly with latitudinal/altitudinal gradients. Here, we review the relevant literature and outline more appropriate sampling designs as well as suitable modelling techniques (e. g. linear mixed models and eigenvector mapping), that will more adequately address and identify the range of factors responsible for the distribution of terrestrial arthropods in Antarctica.

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This study aimed to: (1) assess differences between two quantitative sampling methods of soil microarthropods (visual census vs. stone washing) in ice-free areas located along a latitudinal gradient (from 72 degrees 37'S to 74 degrees 42'S) in northern Victoria Land (Antarctica); (2) furnish preliminary results on the abundance and diversity of mites and springtails in the studied areas. Visual census yielded reliable density estimates for adult collembolans and larger prostigmatic mites but did not detect small species. The study updates the distribution of several mites, including the southernmost record of an Oribatida species at global scale. Species composition was correlated with latitude but the uneven abundance distribution and local high beta-diversity probably reflect habitat fragmentation and population isolation. Under this circumstance nested sampling design should be usefully employed. Priorities and suitable methods for studying terrestrial microarthropod communities in continental Antarctica are discussed.

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The bioavailability of soil arsenic (As) is determined by its speciation in soil solution, i.e., arsenite [As(III)] or arsenate [As(V)]. Soil bioavailability studies require suitable methods to cope with small volumes of soil solution that can be speciated directly after sampling, and thereby minimise any As speciation change during sample collection. In this study, we tested a self-made microcartridge to separate both As species and compared it to a commercially available cartridge. In addition, the diffusive gradient in thin films technique (DGT), in combination with the microcartridges, was applied to synthetic solutions and to a soil spiked with As. This combination was used to improve the assessment of available inorganic As species with ferrihydrite(FH)-DGT, in order to validate the technique for environmental analysis, mainly in soils. The self-made microcartridge was effective in separating As(III) from As(V) in solution with detection by inductively coupled plasma optical emission spectrometry (ICP-OES) in volumes of only 3 ml. The DGT study also showed that the FH-based binding gels are effective for As(III) and As(V) assessment, in solutions with As and P concentrations and ionic strength commonly found in soils. The FH-DGT was tested on flooded and unflooded As spiked soils and recoveries of As(III) and As(V) were 85–104% of the total dissolved As. This study shows that the DGT with FH-based binding gel is robust for assessing inorganic species of As in soils.